There are many applications of video copy detection, such as for copyright control, for monitoring advertisement campaigns of businesses, for monitoring ads of competitors for business intelligence, and for law enforcement investigations.
An existing solution for video copy detection is watermarking. In watermarking, digital artifacts (watermarks) are covertly embedded into certain portions of an original video stream. Using specialized digital processing, the digital artifacts, if they are present in a suspect video stream, can be detected. This signals the presence of the watermarked portions in the suspect video stream, and can serve to infer, to a certain degree, that a copy of the original video stream is present in the suspect video stream.
A problem with watermarking is that only the content that has been watermarked can be detected. Therefore, portions of an original video stream that have not been watermarked cannot be detected as being present in a suspect video stream even if they are indeed present. Since watermarking involves both front-end processing and an up-front cost, it is not always a convenient option. Furthermore, distortion in a suspect video stream can affect the reliability with which watermarks can be detected in the suspect video stream.
As an alternative to watermarking, content-based copy detection can be used in order to detect an original video segment of which there is a copy in the search database, without the need for processing at the video generation or transmission end.
However, existing video copy detection techniques provide inadequate performance when measured in terms of, for example, normalized cost detection rate (NCDR).
Accordingly, there exists in the industry a need to provide improved solutions for content-based video copy detection.